Looking for trouble? Try Bayesian Artificial Intelligence…

Ok, I’ll be honest, I’ve always been into probabilistic methods, for they somehow “fit” into my way of thinking. There is something about probabilistic methods, and probability theory; you are either suitable to work with it or not; you either love the field, or hate it.

I’m the kind of guy who has some love hate relationship with it. I certainly like the field, but the overall concept is so deep and abstract that I can get lost very easily. Something that makes perfect sense seems like Chinese the next day, but I still can’t let go.

On top of that, I’ve been working on integrating probability based methods to my work in data mining and decision support, and finally I found myself working on Bayesian AI. Trust me; it “is” hard. It requires you to cover a vast amount of subjects and even then there is always something missing. Still, I have not given up, and I’m about to reach a point where I can build simple but practical applications for medical informatics. Bayesian AI is basically probabilistic modeling for building (semi)autonomous systems. After Judea Pearl wrote the book Probabilistic Reasoning in Intelligent Systems, an army of researchers rushed to the field, but still the field seems much less crowded compared to well known AI, neural networks etc. If you’d like to have an idea of what I’m talking about; MIT has a very good web page in OpenCourseWare which you can find here . I have been looking around to find some frameworks which I can use, and the work in the field has few complete, well polished outcomes. Most of the projects seems to be dead or incomplete, but there are a few worth mentioning, but I’ll do that later.

Bayesian AI provides a set of very strong tools when you have a heap of raw data and chaos, which is an acceptable definition of health informatics. I’m very clear about one thing; I’m tired of building things that somehow collect and save data. Most of the time what we call information is nothing more than a set of fancy reports, and we are quite far away from using existing data for decision making. I really believe that there exists a requirement for a new generation of tools that will be based on modeling of healthcare domain so that we can forecast the outcomes of our choices, at least at a primitive level. Even the simplest of such tools would make a huge difference. I should say that it is very, very hard to build them, but it seems like a more justified effort than building another version of an already existing EHR system or HIS. There are a lot of bright people working on these fields, why very few people choose to work on modeling and forecasting is a mystery to me.